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Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
Collecting open-source intelligence is achieved in a variety of different ways, [4] such as: Social Media Intelligence, which is acquired from viewing or observing a subjects online social profile activity. Search engine data mining or scraping. Public records checking. Information matching and verification from data broker services.
Weak AI hypothesis: An artificial intelligence system can (only) act like it thinks and has a mind and consciousness. The first one he called "strong" because it makes a stronger statement: it assumes something special has happened to the machine that goes beyond those abilities that we can test. The behaviour of a "weak AI" machine would be ...
Intelligence analysis is the application of individual and collective cognitive methods to weigh data and test hypotheses within a secret socio-cultural context. [1] The descriptions are drawn from what may only be available in the form of deliberately deceptive information; the analyst must correlate the similarities among deceptions and extract a common truth.
Informatics (a combination of the words "information" and "automatic") is the study of computational systems. [1] [2] According to the ACM Europe Council and Informatics Europe, informatics is synonymous with computer science and computing as a profession, [3] in which the central notion is transformation of information.
Intelligence amplification (IA) (also referred to as cognitive augmentation, machine augmented intelligence and enhanced intelligence) is the use of information technology in augmenting human intelligence. The idea was first proposed in the 1950s and 1960s by cybernetics and early computer pioneers.
Distributed Artificial Intelligence (DAI) is an approach to solving complex learning, planning, and decision-making problems.It is embarrassingly parallel, thus able to exploit large scale computation and spatial distribution of computing resources.
The problem of attaining human-level competency at "commonsense knowledge" tasks is considered to probably be "AI complete" (that is, solving it would require the ability to synthesize a fully human-level intelligence), [4] [5] although some oppose this notion and believe compassionate intelligence is also required for human-level AI. [6]